3D surface reconstruction from range slices

Abstract

Research on three-dimensional (3D) surface reconstruction from range slices obtained from range-gated laser imaging system is of significance. 3D surfaces reconstructed based on existing binarization method or centroid method are rough or discontinuous in some circumstances. In this paper we address these problems and develop a 3D surface reconstruction algorithm based on the idea that combining the centroid method with weighted linear interpolation and mean filter. The algorithm consists of three steps. In the first step, interesting regions are extracted from each range slice based on mean filter, and then are merged to derive a single range image. In the second step, the derived range image is denoised and smoothed based on adaptive histogram method, weighted linear interpolation and mean filter method respectively. Finally, nonzero valued pixels in the after processed range image are converted to point cloud according to the range-gated imaging parameters, and then 3D surface meshes are established from the point cloud based on the topological relationship between adjacent pixels in the range image. Experiment is conducted on range slices generated from range-gated laser imaging simulation platform, and the registration result of the reconstructed surface of our method with the original surface of the object shows that the proposed method can reconstruct object surface accurately, so it can be used for the designing of reconstruction and displaying of range-gated laser imaging system, and also can be used for 3D object recognition.